Pass the Splunk Cybersecurity Defense Analyst SPLK-5002 Questions and answers with ExamsMirror

Threat intelligence in Splunk Enterprise Security (ES) enhances SOC capabilities by identifying known attack patterns, suspicious activity, and malicious indicators.

Essential Steps in Developing Threat Intelligence:

Collecting Data from Trusted Sources (A)

Gather data from threat intelligence feeds (e.g., STIX, TAXII, OpenCTI, VirusTotal, AbuseIPDB).

Include internal logs, honeypots, and third-party security vendors.

Analyzing and Correlating Threat Data (C)

Use correlation searches to match known threat indicators against live data.

Identify patterns in network traffic, logs, and endpoint activity.

Operationalizing Intelligence Through Workflows (E)

Automate responses using Splunk SOAR (Security Orchestration, Automation, and Response).

Enhance alert prioritization by integrating intelligence into risk-based alerting (RBA).

The Splunk REST API allows programmatic access to Splunk’s features, helping automate security workflows in a Security Operations Center (SOC).

Key REST API Actions for Automation:

POST for creating new data entries (A)

Used to send logs, alerts, or notable events to Splunk.

Essential for integrating external security tools with Splunk.

GET for retrieving search results (C)

Fetches logs, alerts, and notable event details programmatically.

Helps automate security monitoring and incident response.

Effective case management in Splunk Enterprise Security (ES) helps streamline incident tracking, investigation, and resolution.

How to Optimize Case Management:

Standardizing ticket creation workflows (A)

Ensures consistency in how incidents are reported and tracked.

Reduces manual errors and improves collaboration between SOC teams.

Integrating Splunk with ITSM tools (C)

Automates the process of creating and updating tickets in ServiceNow, Jira, or Remedy.

Enables better tracking of incidents and response actions.

Aggregation policies in Splunk Enterprise Security (ES) are used to group related notable events, reducing alert fatigue and improving incident analysis.

Role of Aggregation Policies in Correlation Searches:

Group Related Notable Events (A)

Helps SOC analysts see a single consolidated event instead of multiple isolated alerts.

Uses common attributes like user, asset, or attack type to aggregate events.

Improves Incident Response Efficiency

Reduces the number of duplicate alerts, helping analysts focus on high-priority threats.

If there is a delay in data being indexed from a remote location, even though the Universal Forwarder (UF) is correctly configured, the issue is likely a queue blockage or network latency.

Steps to Diagnose and Fix Forwarder Delays:

Check Forwarder Logs (splunkd.log) for Queue Issues (A)

Look for messages likeTcpOutAutoLoadBalancedorQueue is full.

If queues are full, events are stuck at the forwarder and not reaching the indexer.

Monitor Forwarder Health Usingmetrics.log

Useindex=_internal source=*metrics.log* group=queueto check queue performance.

Improving Splunk’s indexing performance is crucial for handling large volumes of data efficiently while maintaining fast search speeds and optimized storage utilization.

Methods to Improve Indexing Performance:

Enable Indexer Clustering (A)

Distributes indexing load across multiple indexers.

Ensures high availability and fault tolerance by replicating indexed data.

Optimize Event Breaking Rules (D)

Defines clear event boundaries to reduce processing overhead.

Uses correctLINE_BREAKERandTRUNCATEsettings to improve parsing speed.

Correlation searches in Splunk Enterprise Security (ES) are a critical component of Security Operations Center (SOC) workflows, designed to detect threats by analyzing security data from multiple sources.

Primary Purpose of Correlation Searches:

Identify threats and anomalies: They detect patterns and suspicious activity by correlating logs, alerts, and events from different sources.

Automate security monitoring: By continuously running searches on ingested data, correlationsearches help reduce manual efforts for SOC analysts.

Generate notable events: When a correlation search identifies a security risk, it creates a notable event in Splunk ES for investigation.

Trigger security automation: In combination with Splunk SOAR, correlation searches can initiate automated response actions, such as isolating endpoints or blocking malicious IPs.

Since correlation searches analyze relationships and patterns across multiple data sources to detect security threats, the correct answer is B. To identify patterns and relationships between multiple data sources.

References:

Splunk ES Correlation Searches Overview

Best Practices for Correlation Searches

Splunk ES Use Cases and Notable Events

In Splunk Enterprise Security (ES), notable events are generated by correlation searches, which are predefined searches designed to detect security incidents by analyzing logs and alerts from multiple data sources. Adding additional context to these notable events enhances their value for analysts and improves the efficiency of incident response.

To incorporate additional context, you can:

Use lookup tables to enrich data with information such as asset details, threat intelligence, and user identity.

Leverage KV Store or external enrichment sources like CMDB (Configuration Management Database) and identity management solutions.

Apply Splunk macros orevalcommands to transform and enhance event data dynamically.

Use Adaptive Response Actions in Splunk ES to pull additional information into a notable event.

The correct answer is A. By adding enriched fields during search execution, because enrichment occurs dynamically during search execution, ensuring that additional fields (such as geolocation, asset owner, and risk score) are included in the notable event.

References:

Splunk ES Documentation on Notable Event Enrichment

Correlation Search Best Practices

Using Lookups for Data Enrichment